基于并行蚁群算法的长基线定位方法*

为了降低各个误差源对水声目标导航定位精度的影响,该文将水声目标导航定位问题抽象为带约束条件的非线性优化问题,并论证了最优化表达式参数求解过程与降低误差源干扰的过程具有同一性;设计了并行蚁群算法求其最优解。海试数据处理结果表明,该方法具有收敛速度快、解稳定和定位精度高等优点,能有效地降低各个误差源对水声目标导航定位精度的影响。

Parallel ant colony algorithm for long baseline acoustic positioning

In order to reduce the influence of various error sources on the navigation accuracy of underwater acoustic target, a novel LBL positioning algorithm is proposed, which abstracts the problem of underwater acoustic target navigation as a nonlinear optimization problem with constrained conditions. The analysis indicates that the parameter solving process of the optimization expression has the identity with the process of reducing error source interference. Then, its optimal solution is found by a parallel ant colony algorithm. The experimental results from sea trial data show that the proposed algorithm has the advantages of fast convergence speed, stable solution and high positioning accuracy. It can effectively reduce the influence of various error sources on navigation accuracy of underwater acoustic target.